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Analysis of experimental ECG
Maršánová, Lucie ; Janoušek, Oto (referee) ; Ronzhina, Marina (advisor)
This diploma thesis deals with the analysis of experimental electrograms (EG) recorded from isolated rabbit hearts. The theoretical part is focused on the basic principles of electrocardiography, pathological events in ECGs, automatic classification of ECG and experimental cardiological research. The practical part deals with manual classification of individual pathological events – these results will be presented in the database of EG records, which is under developing at the Department of Biomedical Engineering at BUT nowadays. Manual scoring of data was discussed with experts. After that, the presence of pathological events within particular experimental periods was described and influence of ischemia on heart electrical activity was reviewed. In the last part, morphological parameters calculated from EG beats were statistically analised with Kruskal-Wallis and Tukey-Kramer tests and also principal component analysis (PCA) and used as classification features to classify automatically four types of the beats. Classification was realized with four approaches such as discriminant function analysis, k-Nearest Neighbours, support vector machines, and naive Bayes classifier.
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Game with Hand Gesture Control
Baštek, Jozef ; Žák, Pavel (referee) ; Hradiš, Michal (advisor)
This paper is intended for computer vision usage as a way of human-computer interacion. It covers design and implementation of interface for game controlling by hand gestures and movements, that are captured by camera. It describes and evaluates image segmentation algorithms (background subtraction, thresholding, Bayes' theorem, gaussian model) as well as hand gesture classification algorithms (knowledge-based classification, Hu invariant moments and K-nearest neighours). Implementation includes machanical contruction of camera holder and 3D FPS game as a interface usage demonstration.
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Sleep stage classification
Lacinová, Michaela ; Smital, Lukáš (referee) ; Králík, Martin (advisor)
This bachelor thesis deals with analysis of polysomnography and its methods of measurement in electroencephalography, electromyography and electrooculography in the first part. It comprises an analysis of sleep stages recommended by the AASM. Polysomnographic data are further analysed in the domains of time and frequency, which are evaluated separately. In the second part the data are classified into particular classes using methods of decision trees and k-nearest neighbours in the MATLAB programming environment. These data are evaluated and compared with available literature.
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Detection of atrial fibrilation in long-term ECG
Polcer, Simon ; Kozumplík, Jiří (referee) ; Maršánová, Lucie (advisor)
The bachelor’s thesis deals with the automatic detection of atrial fibrillations in the long-term ECG signals. First, it provides a description of the electrophysiology of the heart, the atrial fibrillation and the automatic methods of their detection. The first method, implemented in this work, is based upon the parameters that were calculated from the irregularities of the RR intervals. The second method uses the stationary wavelet transform and other parameters are computed after the signal transformation. The calculated parameters are subsequently statistically evaluated in the STATISTICA software. Parameters are assessed by the non-parametric Mann-Whitney test, which selects parameters that exhibit statistically significant differences between signals containing atrial fibrillation and sinus rhythm. At the end, the classification is performed by two approaches such as Support vector machine and k-Nearest Neighbours.
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Detection of atrial fibrilation in long-term ECG
Polcer, Simon ; Kozumplík, Jiří (referee) ; Maršánová, Lucie (advisor)
The bachelor’s thesis deals with the automatic detection of atrial fibrillations in the long-term ECG signals. First, it provides a description of the electrophysiology of the heart, the atrial fibrillation and the automatic methods of their detection. The first method, implemented in this work, is based upon the parameters that were calculated from the irregularities of the RR intervals. The second method uses the stationary wavelet transform and other parameters are computed after the signal transformation. The calculated parameters are subsequently statistically evaluated in the STATISTICA software. Parameters are assessed by the non-parametric Mann-Whitney test, which selects parameters that exhibit statistically significant differences between signals containing atrial fibrillation and sinus rhythm. At the end, the classification is performed by two approaches such as Support vector machine and k-Nearest Neighbours.
|
|
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Sleep stage classification
Lacinová, Michaela ; Smital, Lukáš (referee) ; Králík, Martin (advisor)
This bachelor thesis deals with analysis of polysomnography and its methods of measurement in electroencephalography, electromyography and electrooculography in the first part. It comprises an analysis of sleep stages recommended by the AASM. Polysomnographic data are further analysed in the domains of time and frequency, which are evaluated separately. In the second part the data are classified into particular classes using methods of decision trees and k-nearest neighbours in the MATLAB programming environment. These data are evaluated and compared with available literature.
|
|
|
Game with Hand Gesture Control
Baštek, Jozef ; Žák, Pavel (referee) ; Hradiš, Michal (advisor)
This paper is intended for computer vision usage as a way of human-computer interacion. It covers design and implementation of interface for game controlling by hand gestures and movements, that are captured by camera. It describes and evaluates image segmentation algorithms (background subtraction, thresholding, Bayes' theorem, gaussian model) as well as hand gesture classification algorithms (knowledge-based classification, Hu invariant moments and K-nearest neighours). Implementation includes machanical contruction of camera holder and 3D FPS game as a interface usage demonstration.
|
|
|
Analysis of experimental ECG
Maršánová, Lucie ; Janoušek, Oto (referee) ; Ronzhina, Marina (advisor)
This diploma thesis deals with the analysis of experimental electrograms (EG) recorded from isolated rabbit hearts. The theoretical part is focused on the basic principles of electrocardiography, pathological events in ECGs, automatic classification of ECG and experimental cardiological research. The practical part deals with manual classification of individual pathological events – these results will be presented in the database of EG records, which is under developing at the Department of Biomedical Engineering at BUT nowadays. Manual scoring of data was discussed with experts. After that, the presence of pathological events within particular experimental periods was described and influence of ischemia on heart electrical activity was reviewed. In the last part, morphological parameters calculated from EG beats were statistically analised with Kruskal-Wallis and Tukey-Kramer tests and also principal component analysis (PCA) and used as classification features to classify automatically four types of the beats. Classification was realized with four approaches such as discriminant function analysis, k-Nearest Neighbours, support vector machines, and naive Bayes classifier.
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